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Can Large Language Models Understand Context?
Paper • 2402.00858 • Published • 21 -
OLMo: Accelerating the Science of Language Models
Paper • 2402.00838 • Published • 78 -
Self-Rewarding Language Models
Paper • 2401.10020 • Published • 140 -
SemScore: Automated Evaluation of Instruction-Tuned LLMs based on Semantic Textual Similarity
Paper • 2401.17072 • Published • 25
Collections
Discover the best community collections!
Collections including paper arxiv:2405.01525
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FLAME: Factuality-Aware Alignment for Large Language Models
Paper • 2405.01525 • Published • 24 -
DeepSeek-Prover: Advancing Theorem Proving in LLMs through Large-Scale Synthetic Data
Paper • 2405.14333 • Published • 32 -
Transformers Can Do Arithmetic with the Right Embeddings
Paper • 2405.17399 • Published • 51 -
EasyAnimate: A High-Performance Long Video Generation Method based on Transformer Architecture
Paper • 2405.18991 • Published • 12
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Be Yourself: Bounded Attention for Multi-Subject Text-to-Image Generation
Paper • 2403.16990 • Published • 24 -
ViTAR: Vision Transformer with Any Resolution
Paper • 2403.18361 • Published • 51 -
Getting it Right: Improving Spatial Consistency in Text-to-Image Models
Paper • 2404.01197 • Published • 29 -
Bigger is not Always Better: Scaling Properties of Latent Diffusion Models
Paper • 2404.01367 • Published • 19
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Direct Preference Optimization: Your Language Model is Secretly a Reward Model
Paper • 2305.18290 • Published • 43 -
ICDPO: Effectively Borrowing Alignment Capability of Others via In-context Direct Preference Optimization
Paper • 2402.09320 • Published • 6 -
sDPO: Don't Use Your Data All at Once
Paper • 2403.19270 • Published • 38 -
Dueling RL: Reinforcement Learning with Trajectory Preferences
Paper • 2111.04850 • Published • 2
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AtP*: An efficient and scalable method for localizing LLM behaviour to components
Paper • 2403.00745 • Published • 11 -
The Era of 1-bit LLMs: All Large Language Models are in 1.58 Bits
Paper • 2402.17764 • Published • 589 -
MobiLlama: Towards Accurate and Lightweight Fully Transparent GPT
Paper • 2402.16840 • Published • 23 -
LongRoPE: Extending LLM Context Window Beyond 2 Million Tokens
Paper • 2402.13753 • Published • 110
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Griffin: Mixing Gated Linear Recurrences with Local Attention for Efficient Language Models
Paper • 2402.19427 • Published • 52 -
Beyond Language Models: Byte Models are Digital World Simulators
Paper • 2402.19155 • Published • 49 -
StarCoder 2 and The Stack v2: The Next Generation
Paper • 2402.19173 • Published • 130 -
Simple linear attention language models balance the recall-throughput tradeoff
Paper • 2402.18668 • Published • 18